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14 results for “electromagnetic modelling”

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zenodo44/100

DL-RMD: A geophysically constrained electromagnetic resistivity model database for deep learning applications (Dataset)

<p>Deep learning algorithms have shown incredible potential in many applications. The success of these data-hungry methods is largely associated with the availability of large-scale data sets, as millions of observations are often required to achieve acceptable performance levels. Recently, there has been an increased interest in applying deep learning methods to geophysical applications where electromagnetic methods are used to map the subsurface geology by observing variations in the electrical resistivity of the subsurface materials. To date, there are no standardized datasets for electromagnetic methods, which hinders the progress, evaluation, benchmarking, and evolution of deep learning algorithms due to data inconsistency. Therefore, we present a large-scale electrical resistivity model database of a wide variety of geologically plausible and geophysically resolvable subsurface structures for the commonly deployed ground-based and airborne electromagnetic systems. The presented database can potentially be used to build surrogate models of well-known processes and aid in labour intensive tasks. The geophysically constrained property of this database will not only achieve enhanced performance and improved generalization but, more importantly, it will incorporate consistency and credibility in deep learning models. We urge the geophysical community interested in deep learning for electromagnetic methods to utilize the presented database.</p>

opencc-by-4.0Jun 2022View details →
zenodo44/100

Marine time domain electromagnetic data and true model for 2.5D inversion

<p>Dataset contains the description of complex 3D geoelectric model (with bathymetry, curved surfaces of geoelectric layers, target bodies simulated HC deposits,&nbsp;and background inhomogeneities) and marine time domain electromagnetic data calculated via finite element modeling. Noised data sets have been used for geometric 2.5D inversion.</p>

opencc-by-4.0Oct 2022View details →
zenodo44/100

Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure

<p>Accompanying data to journal article</p> <blockquote> <p>Castillo-Reyes, O., Rulff, P., Schankee Um, E., Amor-Martin, A. (2023) Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure. Accepted for publication in Computational Geosciences.</p> </blockquote>

opencc-by-4.0Aug 2023View details →
zenodo40/100

Realistic complex geoelectric model with topography, curved layers with the airborne electromagnetic (AEM) system positions and dBz/dt signals

<p>The uploaded files contain the description of the complex model that is used to provide some computational experiments.It is a realistic complex geoelectric model with topography, curved layers, 3-D objects of complex shape, and a fragment of a real observation system containing several thousand AEM system positions. The observation system file also includes&nbsp;dBz/dt values obtained in the measuring points.</p> <p>The model is described with several archieved text files which format is explained in the &quot;readme.txt&quot; file.</p>

opencc-by-4.0Sep 2021View details →
zenodo36/100

Supplementary Material for "Time-domain modelling of 3-D Earth's and planetary electromagnetic induction effect in ground and satellite observations"

<p>1. Magnetic field residuals from Observatory and Swarm data. Details about data origin and pre-processing are given in the main paper.</p> <p>2. Time series of external Spherical Harmonic coefficients estimated from observatory and satellite data as described in the main paper.</p>

opencc-by-4.0Sep 2020View details →
zenodo36/100

HPC geophysical electromagnetics: a synthetic VTI model with complex bathymetry

<p>Castillo-Reyes, O., de la Puente, J., Cela, E. J.M. (2022) HPC geophysical electromagnetics: a synthetic VTI model with complex bathymetry. Submitted to Energies Journal</p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Electromagnetic Wave Dataset for Strength Degradation Detection in Reinforced Concrete Structures Using RFID Measurements and CNN Model

<p>This dataset comprises 1,800 electromagnetic wave (EM-wave) images collected from three different reinforced concrete beams subjected to varying levels of corrosion. Each image is classified into 'normal' or 'reduced strength' categories based on the beam's structural integrity. Generated through a non-destructive RFID-based monitoring technique, this dataset integrates advanced analyses like 2-D Fourier transforms and fractal dimensions. It is specifically designed to train and validate Convolutional Neural Networks (CNNs) for detecting strength degradation in reinforced concrete structures.</p>

opencc-by-4.0Jul 2024View details →
zenodo36/100

Modeling energetic electron nonlinear wave-particle interactions with electromagnetic ion cyclotron waves

<p>Simulation data set for the JGR paper &quot;Modeling energetic electron nonlinear wave-particle interactions with electromagnetic ion cyclotron waves&quot;. Data formats are in ASCII and Matlab mat file. Data contents are self-explanatory by their file names.</p>

opencc-by-4.0Dec 2018View details →
zenodo32/100

Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs

<p>This archive contains the data used for plots 1, 2, 3, 6 and 7 of the Physics of Plasma paper &quot;Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs&quot; by J.-L. Vay et al (2021).</p> <p>&nbsp;</p> <p>To produce plots 1, 2 and 3, cd into the corresponding directory and run the python script.</p> <p>&nbsp;</p> <p>To produce plots 6 and 7, cd in the directory Figures_6_7 and run the script mkzplots.</p> <p>&nbsp;</p> <p>Simulations were performed on Summit (OLCF) with WarpX Version 19.10-2404-gafa3d4808ff0-dirty (code with slight modification from repo is given in archive warpx_source.tar.gz).</p> <p>&nbsp;</p> <p>Loaded Modules:</p> <p>&nbsp; 1) hsi/5.0.2.p5 &nbsp; 3) lsf-tools/2.0 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 5) DefApps &nbsp; &nbsp; 7) spectrum-mpi/10.3.1.2-20200121 &nbsp; 9) ccache/3.7.9&nbsp; 11) boost/1.66.0&nbsp; 13) hdf5/1.10.4 &nbsp; 15) openblas/0.3.9-omp &nbsp; 17) nano/2.6.3</p> <p>&nbsp; 2) xalt/1.2.1 &nbsp; &nbsp; 4) darshan-runtime/3.1.7 &nbsp; 6) gcc/6.4.0 &nbsp; 8) cuda/10.1.243 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 10) fftw/3.3.8&nbsp; &nbsp; 12) cmake/3.18.2&nbsp; 14) adios2/2.5.0&nbsp; 16) netlib-lapack/3.8.0&nbsp; 18) python/3.6.6-anaconda3-5.3.0</p>

opencc-by-4.0Jan 2021View details →
zenodo32/100

Dataset presented in the recently submitted AGU manuscript "A multi-resolution finite-element approach for global electromagnetic induction modeling with application to southeast China coastal geomagnetic observatory studies"

<p>Dataset presented in the recently submitted AGU paper &quot;A multi-resolution finite-element approach for global electromagnetic induction modeling with application to southeast China coastal geomagnetic observatory studies&quot;</p>

opencc-by-4.0Apr 2022View details →
zenodo32/100

Supplemental Material for the paper "Hamiltonian model for electron heating by electromagnetic waves during magnetic reconnection with a strong guide field"

<p>Video clip showing the trajectories of two close particles in the (x,px) phase space while interacting with a wave.</p> <p>Red and green dots are the particle positions, superimposed to the instantaneous energy levels.</p>

opencc-by-4.0Jul 2024View details →
zenodo32/100

Controlled-source electromagnetic modeling using a versatile secondary electric-field formulation and efficient multigrid-based preconditioner

<p>Models and responses files for the manuscript &quot;<strong>Controlled-source electromagnetic modeling using a versatile secondary electric-field formulation and efficient multigrid-based preconditioner&quot;.</strong></p>

opencc-by-4.0Mar 2023View details →
dryad32/100

Pulsed electromagnetic field (PEMF) transiently stimulates the rate of mineralization in a 3-dimensional ring culture model of osteogenesis

Open the record for dataset details and reuse information.

publicDec 2020View details →
zenodo24/100

Models and data in support of "EMFEM: a parallel 3D modeling code for frequency-domain electromagnetic method using goal-oriented adaptive finite element method"

<p>These directories contain the model and data files for &quot;EMFEM: a parallel 3D modeling code for frequency-domain electromagnetic method using goal-oriented adaptive finite element method&quot;.<br> &nbsp;</p>

opencc-by-4.0Jun 2023View details →

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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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OpenNeuro

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Last verified 2026-04-29Open record